Hands-On Big Data Modeling

Lee, James|Wei, Tao|Mukhiya, Suresh Kumar

ISBN 10: 1788620909 / ISBN 13: 9781788620901

Published by Packt Publishing, 2018

About this Item

Big data modeling is very challenging to handle using traditional database modeling and management systems. This book will teach you how to model big data using the latest and more efficient tools such as ERWIN, ANACONDA (Python), and WEKA to model data.

Seller Inventory # 448328623

Bibliographic Details

• Title: Hands-On Big Data Modeling
• Publisher: Packt Publishing
• Publication Date: 2018
• Language: English
• ISBN 10: 1788620909
• ISBN 13: 9781788620901
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Solve all big data problems by learning how to create efficient data models

Key Features

• Create effective models that get the most out of big data
• Apply your knowledge to datasets from Twitter and weather data to learn big data
• Tackle different data modeling challenges with expert techniques presented in this book

Book Description

Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements.

To start with, you'll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you'll work with structured and semi-structured data with the help of real-life examples. Once you've got to grips with the basics, you'll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You'll also learn to create graph data models and explore data modeling with streaming data using real-world datasets.

By the end of this book, you'll be able to design and develop efficient data models for varying data sizes easily and efficiently.

What you will learn

• Get insights into big data and discover various data models
• Explore conceptual, logical, and big data models
• Understand how to model data containing different file types
• Run through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modeling
• Create data models such as Graph Data and Vector Space
• Model structured and unstructured data using Python and R

Who this book is for

This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.

Table of Contents

1. Introduction to Big Data and Data Management
2. Data Modeling and Data Management platforms for Big Data
3. Defining Data Model
4. Categorizing Data Model
5. Structures of Data Model
6. Modeling Structured Data
7. Modeling with Unstructured Data
8. Modeling with Steaming Data
9. Streaming Sensors Data
10. Concept and Approaches of Big Data Management
11. DBMS to BDMS
12. Big Data Management Services and Vendors
13. Modeling Twitter Feeds using Python
14. Modeling Weather Data Points with Python
15. Modeling IMDB Data Points with Python

About the Author

James Lee is a passionate software wizard working at one of the top Silicon Valley-based start-ups specializing in big data analysis. In the past, he has worked at big companies such as Google and Amazon. In his day job, he works with big data technologies, including Cassandra and Elasticsearch, and is an absolute Docker technology geek and IntelliJ IDEA lover with a strong focus on efficiency and simplicity. Apart from his career as a software engineer, he is keen on sharing his knowledge with others and guiding them, especially in relation to start-ups and programming. He has been teaching courses and conducting workshops on Java programming / IntelliJ IDEA since he was 21. James holds an MS degree in computer science from McGill University and has many years' experience as a teaching assistant in a variety of computer science classes. He also enjoys skiing and swimming, and is a passionate traveler.

Tao Wei is a passionate software engineer who works in a leading Silicon Valley-based big data analysis company. Previously, Tao worked in big IT companies, such as IBM and Cisco. He has intensive experience in designing and building distributed, large-scale systems with proven high availability and reliability. Tao has an MS degree in computer science from McGill University and many years of experience as a teaching assistant in various computer science classes. When not working, he enjoys reading and swimming, and is a passionate photographer.

Suresh Kumar Mukhiya is a PhD candidate currently associated with Western Norway University of Applied Sciences (HVL). He is also a web application developer and big data enthusiast specializing in information systems, model-driven software engineering, big data analysis, and artificial intelligence. He has completed a masters in information systems from the Norwegian University of Science and Technology, along with a thesis in processing mining. He also holds a bachelor's degree in computer science and information technology (BSc.CSIT).